Thanks to algorithms, scientists have created a family tree that provides data on 27 million human beings.
- The purpose of this family tree is to understand the genetic links between individuals across the planet.
- This method is the first that manages to gather so much data and process it with algorithms.
What if each of us could know our Stone Age ancestors? In the review Science, researchers from the University of Oxford explain that they have developed the family tree of humanity as a whole, from a genetic point of view. These scientists have created a method that brings together different genetic and genomic data, analyzed using algorithms. “We have built a huge family tree, a genealogy for all of humanity that models as accurately as possible the history that generated all of the genetic variation that we find in humans today.”explains Dr. Yan Wong, one of the main authors of this study.
Over 27 million ancestors
Eight databases have enabled this feat: they bring together data on human genomes, modern or ancient. A total of 3,609 individual genomic sequences from 215 population groups were used. The ancient genomes included samples found across the world, some over 100,000 years old. In total, this allowed them to create a family tree with over 27 million ancestors. The algorithms predicted where ancestors must be present in these trees to explain genetic variations. After adding location data to these genome samples, the authors used the algorithm to estimate where the ancestors had lived. The results reflect key events in the history of human evolution, such as the migration out of Africa of the first human beings.
Wider applications
For researchers, this genealogical map is intended to be enriched over time, with new genetic data collected. “The dataset could easily contain millions more genomes.”, they say. Furthermore, the lessons learned from this study are not limited to human beings. “The method is valid for most living beings, from orangutans to bacteria, emphasizes Dr. Anthony Wilder Wohns, who initiated this research. It could be particularly beneficial in medical geneticse.” According to him, this could help to better understand the origins of certain pathologies.
.
